Video stabilization is an important video enhancement technology which aims at removing annoying shaky motion from videos. In this paper, we propose an robust and efficient video stabilization algorithm based on inter-frame image matching score. Firstly, image matching is performed by a method combining Maximally Stable Extremal Regions (MSERs) detection algorithm and Features from Accelerated Segment Test (FAST) corner detection algorithm, which can get the matching score and the motion parameters of the frame image. Then, the matching score is filtered to filter out the high frequency component and keep the low frequency component. And the motion compensation is performed on the current frame image according to the ratio of the matching score before and after the filtering to retain the global motion and remove the local jitter. Various classical corner detection operators and region matching operators are compared in experiments. And experimental results illustrate that the proposed method is effective to stabilize translational, rotational, and zooming jitter and robust to local motions, and has the state-of-the-art processing speed to meet the needs of real-time equipment.